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Nvidia announces Jetson Nano 2GB, a single board computer

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Re: Nvidia announces Jetson Nano 2GB, a single board computer

#42
I have a Jetson nano. It's a nice thing for what it is, and the price.

But, the software misses the mark by a lot. It's still based on Ubuntu 18.04.

Want python later than 3.6? Not in the box. A lot of python modules need compiling, and the cpu is what you'd expect. Good for what it is, bad for compiling large numbers or packages.

They run a fancy modern desktop based on the Ubuntu one. Sure, it's Nvidia, gotta be flashy. But that eats a quarter of the memory in the device and make the SOC run crazy hot all the time.

These aren't insurmountable issues, they just left a bad taste in my mouth. In theory I only have to do setup changes once, but it's still a poor experience

Re: Nvidia announces Jetson Nano 2GB, a single board computer

#44
post #24

No WiFi kills it for me

This has WiFi.

> The Gigabit Ethernet port is still there, but unfortunately wireless still didn’t make the cut this time around. So if you need WiFi for your project, count on one of those USB ports being permanently taken up with a dongle.

Re: Nvidia announces Jetson Nano 2GB, a single board computer

#45

This seems like it could be useful for home automation. Is this enough power to do voice recognition? I'm sorry if this is a stupid question, I haven't done anything with ML before.

It may not have the horsepower to actually do the learning, but it takes very little computing power to actually run a realized model that was made w/ machine learning.

Re: Nvidia announces Jetson Nano 2GB, a single board computer

#46

I have a Jetson nano. It's a nice thing for what it is, and the price. But, the software misses the mark by a lot. It's still based on Ubuntu 18.04. Want python later than 3.6? Not in the box. A lot of python modules need compiling, and the cpu is what you'd expect. Good for what it is, bad for compiling large numbers or packages. They run a fancy modern desktop based on the Ubuntu one. Sure, it's Nvidia, gotta be fl…

FWIW, I got a review unit and it ships with a much lighter desktop environment (LXDE) this time and is has a swap file enabled by default. I guess that was needed to ship a 2GB version, but overall it seemed a little better thought out. They also include a wifi dongle in the box.

It still only has Python 3.6, but OpenCV and numpy are pre-installed correctly this time so you don't have to compile them which is an improvement.

Re: Nvidia announces Jetson Nano 2GB, a single board computer

#47

Earlier quoted context omitted.

This has WiFi.

> The Gigabit Ethernet port is still there, but unfortunately wireless still didn’t make the cut this time around. So if you need WiFi for your project, count on one of those USB ports being permanently taken up with a dongle.

NVidia at https://www.nvidia.com/en-us/autonomous-machines/embedded-sy... :

> connectivity: Gigabit Ethernet, 802.11ac wireless[1]

> [1] Not initially available in all regions

whatever the footnote means

Re: Nvidia announces Jetson Nano 2GB, a single board computer

#49
post #14

Earlier quoted context omitted.

As usual, the hardware is way ahead of software.

This isn't true. I personally can use this now, and I now 5 or 6 people who have been trying to do stuff using the Intel USB accelerator or Google Coral who I expect will switch to this at this price point. Only the MAIX platform has a price advantage over this now, and the software is much less mature.

The use case between K210 and Jetson systems is quite different. I've used the Maix Dock as a smart controller for a custom CNC system, and it performs beautifully. The Jetson line is more suited to systems that are video heavy (low latency, multiple feeds, mixing, processing, etc). The Maix boards just don't have the RAM to deal with that; I've only been able to handle two incoming video streams at low resolution.

That being said, programming the Maix is a piece of cake. The Jetson Nano was very challenging to deal with; the software is unstable in many cases, and the levels of abstraction are all mixed up, and discovering which Nvidia tools to use is an absolute pain (Gstreamer vs DeepStream vs ARGUS vs whatever else Nvidia pumps out this year). Also, I had way better support from the Maix community than from Nvidia. Nvidia's support model seems to be "unless you're spending tens of thousands of dollars, go pound sand, maybe a volunteer on our forums will help you, if anyone knows what's actually going on here."

Nvidia just has too much software, too little documentation, and holds onto their secret sauce so tightly that doing anything is a true pain.

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